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Found 52 Skills
Use this skill when users need to extract text from images, PDFs, or documents. Supports URLs and local files. Returns structured JSON containing recognized text.
PDF manipulation toolkit. Extract text/tables, create PDFs, merge/split, fill forms, for programmatic document processing and analysis.
Read and analyze academic papers from Zotero library. Use when the user requests to read, access, or analyze a paper by title, author, or topic from their Zotero library. Automatically searches Zotero, converts PDFs to markdown, saves to Notes/PaperInMarkdown, and provides analysis.
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Translate English text files (.txt, .md) to Chinese for language learning and translation practice. Use when the user asks to translate a text file to Chinese, create a Chinese version of an English document, or generate bilingual materials for translation training. The translation preserves sentence structure and combines broken sentences into complete lines.
Extract text from images and PDFs using Mistral OCR API. Convert scanned documents to Markdown, JSON, or plain text. No external dependencies required. Use when you need OCR, extract text from images, convert PDFs to markdown, or digitize documents.
Crawl WeChat Official Account articles, supporting full-text extraction, mixed text and image layout, local image download, and summary generation. Call this when you need to access WeChat Official Account links and convert them to Markdown.
Extract methodologies from documents or examples to create executable skills
Implement optimal chunking strategies in RAG systems and document processing pipelines. Use when building retrieval-augmented generation systems, vector databases, or processing large documents that require breaking into semantically meaningful segments for embeddings and search.
Use Desktop Commander MCP (typically tools like `mcp__desktop-commander__*`) to manage local files and long-running processes: read/write/search files, apply precise edits, work with Excel/PDFs, run terminal commands and interact with REPLs (Python/Node/SSH/DB), inspect/terminate processes, and review tool call history. Use when the task requires doing real work on the machine (editing code/configs, searching a repo, analyzing CSV/Excel, generating/modifying PDFs, running commands with streaming output).
Integrate with Affinda's document AI API to extract structured data from documents (invoices, resumes, receipts, contracts, and custom types). Covers authentication, client libraries (Python, TypeScript), structured outputs with Pydantic models and TypeScript interfaces, webhooks, upload patterns, and the full documentation map. Use when building integrations that parse, classify, or extract data from documents using Affinda.
Build a section-by-section claim–evidence matrix (`outline/claim_evidence_matrix.md`) from the outline and paper notes. **Trigger**: claim–evidence matrix, evidence mapping, 证据矩阵, 主张-证据对齐. **Use when**: 写 prose 之前需要把每个小节的可检验主张与证据来源显式化（outline + paper notes 已就绪）。 **Skip if**: 缺少 `outline/outline.yml` 或 `papers/paper_notes.jsonl`。 **Network**: none. **Guardrail**: bullets-only（NO PROSE）；每个 claim 至少 2 个证据来源（或显式说明例外）。